Abstract
In this paper, a private searching protocol on MapReduce is introduced and formalized within the Mapping-Filtering-Reducing framework. The idea behind of our construction is that a map function Map is activated to generate (key, value) pairs; an intermedial filtering protocol is invoked to filter (key, value) pairs according to a query criteria; a reduce function Reduce is then applied to aggregate the resulting (key, value) pairs generated by the filter. The map function Map and the reduce function Reduction are inherently derived from the MapReduce program while the intermedial filtering algorithm is constructed from the state-of-the-art filtering protocol which in turn can be constructed from a Bloom-Filter with Storage and an additively homomorphic public-key encryption scheme. We show that if the underlying additively homomorphic public-key encryption is semantically secure, then the proposed private searching protocol on MapReduce is semantically secure.
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References
Armbrust, M., Fox, A., Griffith, R., Joseph, A.D., Katz, R.H., Konwinski, A., Lee, G., Patterson, D.A., Rabkin, A., Stoica, I., Zaharia, M.: Above the Clouds: A Berkeley View of Cloud Computing, Technical Report No. UCB/EECS-2009-28
Boneh, D., Kushilevitz, E., Ostrovsky, R., Skeith III, W.E.: Public Key Encryption That Allows PIR Queries. In: Menezes, A. (ed.) CRYPTO 2007. LNCS, vol. 4622, pp. 50–67. Springer, Heidelberg (2007)
Dean, J., Ghemawat, S.: MapReduce: Simplified Data Processing on Large Clusters. In: OSDI 2004, pp. 137–150 (2004)
Dean, J., Ghemawat, S.: MapReduce: simplified data processing on large clusters. ACM Commun. 51(1), 107–113 (2008)
Dean, J., Ghemawat, S.: MapReduce: a flexible data processing tool. CACM Commun. 53(1), 72–77 (2010)
Grossman, R.L.: The Case for Cloud Computing. IT Professional 11(2), 23–27 (2009)
Grossman, R.L., Gu, Y., Sabala, M., Zhang, W.: Compute and storage clouds using wide area high performance networks. Future Generation Comp. Syst. 25(2), 179–183 (2009)
Ostrovsky, R., Skeith III, W.E.: Private Searching on Streaming Data. In: Shoup, V. (ed.) CRYPTO 2005. LNCS, vol. 3621, pp. 223–240. Springer, Heidelberg (2005)
Ostrovsky, R., Skeith III, W.E.: Private Searching on Streaming Data. J. Cryptology 20(4), 397–430 (2007)
Paillier, P.: Public-Key Cryptosystems Based on Composite Degree Residuosity Classes. In: Stern, J. (ed.) EUROCRYPT 1999. LNCS, vol. 1592, pp. 223–238. Springer, Heidelberg (1999)
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Zhu, H., Bao, F. (2010). Private Searching on MapReduce. In: Katsikas, S., Lopez, J., Soriano, M. (eds) Trust, Privacy and Security in Digital Business. TrustBus 2010. Lecture Notes in Computer Science, vol 6264. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15152-1_9
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DOI: https://doi.org/10.1007/978-3-642-15152-1_9
Publisher Name: Springer, Berlin, Heidelberg
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